Congressional & Presidential Tweets About COVID-19

Curious what congress and Trump are saying about the coronavirus?

This analysis takes a look at the number, the positive and negative sentiment, and the content of the tweets, for each party and how that’s evolving over time since February 1, 2020.

I utilize open data hosted online. In particular, big thanks to Alex Litel who created the Tweets of Congress repo, where I pulled congressional tweets from, and the folks running Trump Twitter Archive, where I pulled Trump’s tweets from.

prep data

load packages

library(tidyverse)
library(jsonlite)
library(tidytext)
library(wordcloud)
library(webshot)

define palettes

palette4 = wesanderson::wes_palette("Zissou1", 4, "continuous")
palette4 = c(palette4[1], palette4[2], palette4[4], palette4[3])
palette5 = wesanderson::wes_palette("Zissou1", 5, "continuous")
palette2 = c(palette5[2], palette5[4])

load congress twitter handles

• US Senate Information
• US House Information
• Congressional Twitter Handles

congress_twitter = read.csv("~/Documents/code/US-Congress/116thCongress/116Congress.csv", stringsAsFactors = FALSE) %>%
  rename("name" = Wikipedia..Names) %>%
  gather(handle_type, twitter_handle, ODU.WSDL, CSPAN, TweetCongress, Github) %>%
  select(name, handle_type, twitter_handle) %>%
  mutate(twitter_handle = tolower(twitter_handle),
         twitter_handle = ifelse(twitter_handle == "", NA, twitter_handle),
         name = gsub("<e9>", "é", `Encoding<-`(name, "latin1"), fixed = TRUE),
         name = gsub("<e1>", "á", `Encoding<-`(name, "latin1"), fixed = TRUE),
         name = gsub("<fa>", "ú", `Encoding<-`(name, "latin1"), fixed = TRUE),
         name = gsub("<ed>", "í", `Encoding<-`(name, "latin1"), fixed = TRUE),
         name = gsub("é", "e", name),
         name = gsub("á", "a", name),
         name = gsub("ú", "u", name),
         name = gsub("í", "i", name),
         name = trimws(name)) %>%
  extract(name, c("first", "last"), "([A-Za-z]{1}).* (.*)", remove = FALSE) %>%
  spread(handle_type, twitter_handle)

congress = read.csv("~/Documents/code/us-senate/us-senate/data/us-senate.csv", stringsAsFactors = FALSE) %>%
  bind_rows(read.csv("~/Documents/code/us-house/us-house/data/us-house.csv", stringsAsFactors = FALSE)) %>%
  select(state_name, title, party, name, gender, ethnicity, twitter_handle) %>%
  mutate(twitter_handle = tolower(twitter_handle),
         twitter_handle = ifelse(twitter_handle == "", NA,
                          ifelse(twitter_handle == "housedemocrats", NA,
                          ifelse(twitter_handle == "senatorloeffler?lang=en", NA, twitter_handle))),
         name = gsub("é", "e", name),
         name = gsub("á", "a", name),
         name = gsub("ú", "u", name),
         name = gsub("í", "i", name),
         name = trimws(name)) %>%
  extract(name, c("first", "last"), "([A-Za-z]{1}).* (.*)", remove = FALSE)

congress_info = full_join(congress, congress_twitter, by = c("first", "last")) %>%
  gather(handle_type, twitter_handle, twitter_handle, ODU.WSDL, CSPAN, TweetCongress, Github) %>%
  select(state_name, title, party, first, last, gender, ethnicity, twitter_handle) %>%
  group_by(first, last) %>%
  fill(state_name, title, party, gender, ethnicity, twitter_handle, .direction = "updown") %>%
  unique() %>%
  filter(!is.na(state_name)) %>%
  ungroup() %>%
  mutate(last = tolower(last))

load congressional tweets

• Tweets of Congress, updated daily
• select tweets containing the following terms: corona|virus|covid|flu

pull to update repo

cd ~/Documents/code/congresstweets
git pull origin master

## From https://github.com/alexlitel/congresstweets
##  * branch            master     -> FETCH_HEAD
## Already up to date.

load the files

file_dir = "~/Documents/code/congresstweets/data"
file_pattern = "2020-0[2-3]{1}-.*.json"
file_list = list.files(file_dir, pattern = file_pattern)

tweets_temp = data.frame()

for (file in file_list) {
  temp = tryCatch(jsonlite::stream_in(file(file.path(file_dir, file)), verbose = FALSE), error = function(e) message(file))

  tweets_temp = rbind(tweets_temp, temp)
  rm(temp)
}

tweets_all = tweets_temp %>%
  rename("twitter_handle" = screen_name) %>%
  select(twitter_handle, time, text) %>%
  mutate(twitter_handle = tolower(twitter_handle),
         text = tolower(text)) %>%
  filter(grepl("corona|virus|covid|flu", text))

find missing congressional twitter handles

missing = tweets_all %>% 
  left_join(., congress_info) %>%
  filter(is.na(last)) %>%
  select(twitter_handle) %>%
  unique()

last_names = congress_info %>%
  ungroup() %>%
  select(last) %>%
  unique() %>%
  mutate(last = tolower(last))

missing$last <- sapply(missing$twitter_handle, function(handle) {
  last <- last_names$last[sapply(last_names$last, grepl, handle)]
  }) 

missing %>%
  unnest(last, keep_empty = TRUE) %>%
  mutate(first = toupper(substring(twitter_handle, 1, 1)),
         last = ifelse(is.na(last), "", last)) %>%
  write.csv(., "missing.csv", row.names = FALSE)

missing_edited = read.csv("missing_edited.csv", stringsAsFactors = FALSE)

congress_full = congress_info %>%
  full_join(., missing_edited, by = c("first", "last")) %>%
  gather(var, twitter_handle, contains("twitter_handle")) %>%
  select(-var) %>%
  unique() %>%
  filter(!is.na(twitter_handle)) %>%
  mutate(party = ifelse(party.y == "" | is.na(party.y), party.x, party.y)) %>%
  select(-c(party.x, party.y)) %>%
  unique() %>%
  filter(!is.na(party))

congress_tweets = tweets_all %>%
  left_join(., congress_full) %>%
  mutate(time = lubridate::as_date(time),
         week = lubridate::floor_date(time, "week"),
         month = lubridate::floor_date(time, "month"))

# congress_tweets %>%
#   filter(is.na(party)) %>%
#   select(twitter_handle) %>%
#   unique()

load trump tweets

• Trump Tweets
• Trump Twitter Archive

get_tweets = function(year, fromJSON = TRUE) {
  ## build and send request
  url <- paste0(
    "http://trumptwitterarchive.com/",
    "data/realdonaldtrump/",
    year,
    ".json"
  )
  ## response object
  r <- httr::GET(url)
  ## check html status
  httr::warn_for_status(r)
  ## if fromJSON then convert to list otherwise return response object
  if (fromJSON) {
    r <- httr::content(r, "text")
    ## if html return empty data frame
    if (grepl("^\\<\\!DOCTYPE", r)) {
      r <- data.frame()
    } else {
      r <- jsonlite::fromJSON(r)
    }
  }
  r
}

trump_tweets = get_tweets(year = 2020) %>%
  mutate(twitter_handle = "realdonaldtrump",
         time = as.POSIXct(created_at, format = "%a %b %d %H:%M:%S %z %Y"),
         time = lubridate::as_date(time),
         week = lubridate::floor_date(time, "week"),
         month = lubridate::floor_date(time, "month"),
         party = "trump") %>%
  select(twitter_handle, text, time, week, month, party) %>%
  filter(grepl("2020-02|2020-03", month)) %>%
  mutate(text = tolower(text)) %>%
  filter(grepl("corona|virus|covid|flu", text))

merge tweets

tweets = bind_rows(congress_tweets, trump_tweets)

ignore_root_words = "http|.com|img|jpg|video|live|index|[0-9]|corona|covid|vid|ncov|aspx|utm|t.co|png"
ignore_words = c("rt", "amp", "qt", "pu", "tag", "i'm", "it's", "i’m", "it’s")

define wordcloud function

plot_tweets = function(data, party=NULL, start_date=NULL, duration=NULL, n_words=50, n_colors=6, size=.4) {
  
  data = data %>%
      mutate(time = lubridate::as_date(time))
  
  if (!is.null(party)) {
    data = data %>%
      filter(party == !!party)
  }
  
  if (!is.null(start_date)) {
    if (!is.null(duration)) {
      data = data %>%
        filter(time >= start_date & time <= lubridate::date(start_date) + lubridate::days(duration))
    } else {
      data = data %>%
        filter(time >= start_date)
    }
  }
  
  palette = wesanderson::wes_palette("Zissou1", n_colors, "continuous")
  
  plot = data %>%
    select(text) %>%
    unnest_tokens(word, text) %>%
    count(word, sort = TRUE) %>%
    anti_join(stop_words, by = "word") %>%
    filter(!grepl(ignore_root_words, word)) %>%
    filter(!word %in% ignore_words) %>%
    slice(1:n_words) %>%
    mutate(color = ntile(n, n_colors)) %>%
    mutate(color1 = plyr::mapvalues(color, from = 1:n_colors, to = palette)) %>%
    wordcloud2::wordcloud2(., size = size, shape = 'rectangle',
                          fontFamily = "futura", fontWeight = "normal",
                          color = .$color1)
  
  return(list(plot = plot, data = data))
}

number of tweets

daily

tweets %>%
  filter(!is.na(party)) %>%
  ggplot(aes(time, fill = party)) +
  geom_bar(stat = "count") +
  scale_fill_manual(name = "", values = palette4) +
  labs(x = "", y = "number of tweets\n") +
  theme_minimal(base_size = 14) +
  theme(legend.position = "top")

tweets %>%
  filter(!is.na(party)) %>%
  ggplot(aes(time, color = party)) +
  geom_line(stat = "count") +
  scale_color_manual(name = "", values = palette4) +
  labs(x = "", y = "number of tweets\n") +
  theme_minimal(base_size = 14) +
  theme(legend.position = "top")

weekly

tweets %>%
  filter(!is.na(party)) %>%
  ggplot(aes(week, fill = party)) +
  geom_bar(stat = "count") +
  scale_fill_manual(name = "", values = palette4) +
  labs(x = "", y = "number of tweets\n") +
  theme_minimal(base_size = 14) +
  theme(legend.position = "top")

tweets %>%
  filter(!is.na(party)) %>%
  ggplot(aes(week, color = party)) +
  geom_line(stat = "count") +
  scale_color_manual(name = "", values = palette4) +
  labs(x = "", y = "number of tweets\n") +
  theme_minimal(base_size = 14) +
  theme(legend.position = "top")

sentiment of tweets

overall

sentiments = tweets %>%
  unnest_tokens(word, text) %>%
  inner_join(tidytext::get_sentiments("bing")) %>%
  anti_join(stop_words, by = "word") %>%
  filter(!grepl(ignore_root_words, word)) %>%
  filter(!word %in% ignore_words) %>%
  filter(!word == "trump") %>%
  group_by(party) %>%
  count(word, sentiment, sort = TRUE) %>%
  filter(party %in% c("democrat", "republican", "trump")) %>%
  #group_by(sentiment, party, month) %>%
  top_n(20) %>%
  group_by(party) %>%
  arrange(n) %>%
  mutate(order = row_number())

sentiments %>%
  ggplot(aes(drlib::reorder_within(word, n, party), n, fill = sentiment)) +
  geom_col() +
  drlib::scale_x_reordered() +
  facet_wrap(~party, scales = "free") +
  labs(y = "\nnumber of times tweeted",
       x = NULL) +
  coord_flip() +
  scale_fill_manual(values = palette2) +
  theme_minimal(base_size = 14) +
  theme(legend.position = "top")

by month

sentiments = tweets %>%
  unnest_tokens(word, text) %>%
  inner_join(tidytext::get_sentiments("bing")) %>%
  anti_join(stop_words, by = "word") %>%
  filter(!grepl(ignore_root_words, word)) %>%
  filter(!word %in% ignore_words) %>%
  filter(!word == "trump") %>%
  mutate(month = ifelse(month == "2020-02-01", "february", "march")) %>%
  group_by(party, month) %>%
  count(word, sentiment, sort = TRUE) %>%
  filter(party %in% c("democrat", "republican", "trump")) %>%
  #group_by(sentiment, party, month) %>%
  top_n(20) %>%
  group_by(party, month) %>%
  arrange(n) %>%
  mutate(order = row_number())

sentiments %>%
  ggplot(aes(drlib::reorder_within(word, n, c("party", "month")), n, fill = sentiment)) +
  geom_col() +
  drlib::scale_x_reordered() +
  facet_wrap(month~party, scales = "free") +
  labs(y = "\nnumber of times tweeted",
       x = NULL) +
  coord_flip() +
  scale_fill_manual(values = palette2) +
  theme_minimal(base_size = 14) +
  theme(legend.position = "top")

content by month

democrats

February

d = plot_tweets(tweets, party = "democrat", start_date = "2020-02-01", duration = 29, n_words = 100, size = .4)
htmlwidgets::saveWidget(d$plot,"d.html", selfcontained = FALSE)
webshot("d.html","dm1.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 2015

March

d = plot_tweets(tweets, party = "democrat", start_date = "2020-03-01", duration = 31, n_words = 100, size = .4)
htmlwidgets::saveWidget(d$plot,"d.html", selfcontained = FALSE)
webshot("d.html","dm2.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 7820

republicans

February

r = plot_tweets(tweets, party = "republican", start_date = "2020-02-01", duration = 29, n_words = 100, size = .4)
htmlwidgets::saveWidget(r$plot,"r.html", selfcontained = FALSE)
webshot("r.html","rm1.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 1160

March

r = plot_tweets(tweets, party = "republican", start_date = "2020-03-01", duration = 31, n_words = 100, size = .4)
htmlwidgets::saveWidget(r$plot,"r.html", selfcontained = FALSE)
webshot("r.html","rm2.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 6992

trump

February

t = plot_tweets(tweets, party = "trump", start_date = "2020-02-01", duration = 29, n_words = 100, size = .4)
htmlwidgets::saveWidget(t$plot,"t.html", selfcontained = FALSE)
webshot("t.html","tm1.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 28

March

t = plot_tweets(tweets, party = "trump", start_date = "2020-03-01", duration = 31, n_words = 100, size = .4)
htmlwidgets::saveWidget(t$plot,"t.html", selfcontained = FALSE)
webshot("t.html","tm2.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 81

content by week

democrats

Feb 1 - Feb 7

d = plot_tweets(tweets, party = "democrat", start_date = "2020-02-01", duration = 7)
htmlwidgets::saveWidget(d$plot,"d.html", selfcontained = FALSE)
webshot("d.html","d1.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 212

Feb 8 - Feb 14

d = plot_tweets(tweets, party = "democrat", start_date = "2020-02-08", duration = 7)
htmlwidgets::saveWidget(d$plot,"d.html", selfcontained = FALSE)
webshot("d.html","d2.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 180

Feb 15 - Feb 20

d = plot_tweets(tweets, party = "democrat", start_date = "2020-02-15", duration = 7)
htmlwidgets::saveWidget(d$plot,"d.html", selfcontained = FALSE)
webshot("d.html","d3.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 110

Feb 20 - Feb 26

d = plot_tweets(tweets, party = "democrat", start_date = "2020-02-20", duration = 7)
htmlwidgets::saveWidget(d$plot,"d.html", selfcontained = FALSE)
webshot("d.html","d4.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 928

Feb 27 - Mar 4

d = plot_tweets(tweets, party = "democrat", start_date = "2020-02-27", duration = 7)

htmlwidgets::saveWidget(d$plot,"d.html", selfcontained = FALSE)
webshot("d.html","d5.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 2840

Mar 5 - Mar 11

d = plot_tweets(tweets, party = "democrat", start_date = "2020-03-05", duration = 7)

htmlwidgets::saveWidget(d$plot,"d.html", selfcontained = FALSE)
webshot("d.html","d6.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 4983

Mar 12 - Mar 18

d = plot_tweets(tweets, party = "democrat", start_date = "2020-03-12", duration = 7)

htmlwidgets::saveWidget(d$plot,"d.html", selfcontained = FALSE)
webshot("d.html","d7.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 2935

republicans

Feb 1 - Feb 7

r = plot_tweets(tweets, party = "republican", start_date = "2020-02-01", duration = 7)
htmlwidgets::saveWidget(r$plot,"r.html", selfcontained = FALSE)
webshot("r.html","r1.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 140

Feb 8 - Feb 14

r = plot_tweets(tweets, party = "republican", start_date = "2020-02-08", duration = 7, size = .3)
htmlwidgets::saveWidget(r$plot,"r.html", selfcontained = FALSE)
webshot("r.html","r2.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 166

Feb 15 - Feb 20

r = plot_tweets(tweets, party = "republican", start_date = "2020-02-15", duration = 7)
htmlwidgets::saveWidget(r$plot,"r.html", selfcontained = FALSE)
webshot("r.html","r3.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 88

Feb 20 - Feb 26

r = plot_tweets(tweets, party = "republican", start_date = "2020-02-20", duration = 7)
htmlwidgets::saveWidget(r$plot,"r.html", selfcontained = FALSE)
webshot("r.html","r4.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 482

Feb 27 - Mar 4

r = plot_tweets(tweets, party = "republican", start_date = "2020-02-27", duration = 7)

htmlwidgets::saveWidget(r$plot,"r.html", selfcontained = FALSE)
webshot("r.html","r5.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 2966

Mar 5 - Mar 11

r = plot_tweets(tweets, party = "republican", start_date = "2020-03-05", duration = 7)

htmlwidgets::saveWidget(r$plot,"r.html", selfcontained = FALSE)
webshot("r.html","r6.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 3754

Mar 12 - Mar 18

r = plot_tweets(tweets, party = "republican", start_date = "2020-03-12", duration = 7)

htmlwidgets::saveWidget(r$plot,"r.html", selfcontained = FALSE)
webshot("r.html","r7.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 2520

trump

Feb 1 - Feb 7

t = plot_tweets(tweets, party = "trump", start_date = "2020-02-01", duration = 7)
htmlwidgets::saveWidget(t$plot,"t.html", selfcontained = FALSE)
webshot("t.html","t1.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 2

Feb 8 - Feb 14

t = plot_tweets(tweets, party = "trump", start_date = "2020-02-08", duration = 7, size = .3)
htmlwidgets::saveWidget(t$plot,"t.html", selfcontained = FALSE)
webshot("t.html","t2.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 1

Feb 15 - Feb 20

t = plot_tweets(tweets, party = "trump", start_date = "2020-02-15", duration = 7)
htmlwidgets::saveWidget(t$plot,"t.html", selfcontained = FALSE)
webshot("t.html","t3.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 1

Feb 20 - Feb 26

t = plot_tweets(tweets, party = "trump", start_date = "2020-02-20", duration = 7)
htmlwidgets::saveWidget(t$plot,"t.html", selfcontained = FALSE)
webshot("t.html","t4.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 18

Feb 27 - Mar 4

t = plot_tweets(tweets, party = "trump", start_date = "2020-02-27", duration = 7)
htmlwidgets::saveWidget(t$plot,"t.html", selfcontained = FALSE)
webshot("t.html","t5.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 28

Mar 5 - Mar 11

t = plot_tweets(tweets, party = "trump", start_date = "2020-03-05", duration = 7)
htmlwidgets::saveWidget(t$plot,"t.html", selfcontained = FALSE)
webshot("t.html","t6.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 50

Mar 12 - Mar 18

t = plot_tweets(tweets, party = "trump", start_date = "2020-03-12", duration = 7)
htmlwidgets::saveWidget(t$plot,"t.html", selfcontained = FALSE)
webshot("t.html","t7.png", vwidth = 500, vheight = 400, zoom = 2)

Number of tweets = 37